How Small And Midsize Industrial Manufacturers Can Strengthen Industry Competitiveness

Georg Kube

Part 2 of the “Digitally Transforming Industries” series

Small and midsize industrial manufacturers are part of a vibrant global market that is powering entire economies. Whether these firms produce goods, equipment, parts, machinery, or chemicals, nearly every large original equipment manufacturer (OEM) in a variety of industries relies on them to function effectively and deliver the high quality that consumers expect. Many have risen to the challenge by igniting tremendous growth with lean operations and attention to value delivery.

Although small and midsize businesses (SMB) in the industrial machinery and components (IM&C) industry are highly influential in most markets, they are not a small version of large manufacturers. Because SMBs are, for the most part, OEM suppliers, they must comply with processes imposed by the manufacturing client and ensure that their offering fits within the design requirement of the final product.

To add value to their contribution in their relationship with OEMs, according to IDC’s industry brief sponsored by SAP, “Manufacturing: Small and Midsize Industrial Machinery and Components Manufacturers Are Using Technology to Make a Difference,” IM&C firms understand and accept the importance of advanced technology. Roughly one-third of SMBs agreed that digital technology can help grow revenue, improve efficiency, and manage costs. In addition, the majority believe that adopting such innovations can lead to competitive differentiation.

attitudes-informing-small-and-midsize-imc-manufacturer-technology-investment

Digital transformation challenges the box that defines IM&C firms

Given the availability and affordability of digital technology of all kinds, it’s reasonable for even the smallest firms to envision and prepare for data-driven operations. By connecting internal and external activities on the same technology platform, operators, designers, customers, and adjacent partners can share information and analyze the progress of the entire product development and manufacturing lifecycle – from concept and design to production, installation, and performance feedback.

The value of digital technology in IM&C goes beyond real-time monitoring, collaboration, and advanced analytics to deliver high-quality products. It can also serve as a springboard for calculated actions that enable further monetization, business model innovation, and value.

  • Add to the customers’ cash flow. Embedding sensors into product parts can help OEMs monitor the production process. Going a step further, firms can empower OEMs to decipher opportunities that are hiding in the data, giving IM&C firms a chance to seize new competitive advantages. According to the IDC report, “tools to manage receivables, monitor expenses, and even optimize team composition can dramatically improve both cash position and service delivery effectiveness.”
  • Expand product and service scope to contribute more value to OEMs. While incorporating new technology into processes and products may be regarded as revolutionary, it can take existing capabilities to improve value contribution in the OEM relationship and introduce new revenue streams. For example, small and midsize IM&C businesses can move quality management and service execution to the cloud so they can seek opportunities to increase their product scope from component to assembly or from small assembly to larger assembly.
  • Contribute more to the OEM business network. Small and midsize companies can partner with the rest of their clients’ networks to offer more comprehensive products and services. The resulting higher-value solution can bring higher margins and help the OEM digitally transform itself without disrupting the value chain and its profitability.

IM&C SMBs can redefine products and revenue sources for the entire value chain

Better customer experiences, products, and competitive positioning are always a compelling formula for OEMs when choosing an IM&C firm as a partner. But at the same time, these capabilities can create a foundation for revenue growth, which is a top priority for SMBs cited in the IM&C-focused IDC study.

Cloud-based services are making it easier for SMBs to invest in digitization. This subscription-based, affordable approach to digital transformation provides an opportunity to build out additional offerings and move significant investment away from technology and toward intellectual property and innovation. Not only will this approach empower IM&C SMBs to work the OEM sector, but it will also open the door to new opportunities for monetization and in adjacent industries never before considered by their clients nor themselves.

To learn how your business can better prepare for the digital economy, check out IDC’s Industry Brief, “Manufacturing: Small and Midsize Industrial Machinery and Components Manufacturers Are Using Technology to Make a Difference.” Be sure to check every Tuesday for new installments to our blog series “Digitally Transforming Industries” to explore the various leadership roles in today’s growing small and midsize companies.


Georg Kube

About Georg Kube

Georg Kube is the global head of SAP’s industry business unit for the Industrial Machinery & Components industry. He is responsible for defining industry-relevant solutions based on SAP’s complete portfolio of products and technologies, bringing them to market, and driving business in the regional units.

The Sky Is Not Falling In Banking (I Promise)

Karen McDermott

Call it hype, paranoia, sport: no matter where you go, you can find a “thought leadership” article from a talking head, consultant, technologist, or “fintech founder” who says that a fintech or a challenger like Amazon is going take down banking. I get it – fear sells. However, as I’ve alluded to in the past – my money’s on banking, and it still is.

The latest hype is how AI is going to take away all of our jobs – not just in banking, but everywhere. I read an article today entitled “AI Could Kill 2.5 Million Financial Jobs – And Save Banks $1 Trillion” and I shared it on Twitter. The immediate feedback from IDC analyst @JamesWester was that the title didn’t match the content of the article.  Evidently, there was a math calculation that the author got wrong. We can give them a pass on that. After all, not everyone is as good with numbers as the bankers.

But in terms of the hype headline, we’ve gotten to this place where fear-inducing headlines are the mouse trap cheese in the multimedia war for clicks. Isn’t the value of this technology interesting enough to talk about without scaring everyone to death? I think it is.

Let’s take a deep breath.  The premise of the article is on point in conceptual terms. For example, AI is already feeding machine learning (ML) to automate certain manual processes in banking that are error-prone and subject to regulatory scrutiny. Automating the process using ML in trade reconciliation, for example, will lead to lower operating costs (headcount) and higher accuracy rates, which could result in less regulatory risk as well.

Yes, banks are going to lower costs by reducing manual labor, and that will result in fewer jobs. However, as we have seen in banking over the last two decades, certain jobs that require outdated skills become eliminated and new jobs take their place – so that things can be done the new, and presumably better, way.

Light at the end of the tunnel

Technology departments in banks have grown dramatically over the last two decades and at accelerating speeds in the last five years. The CIO has a major seat at the table, which never happened in the old days. That has changed dramatically since the digital revolution began, and it accelerated after the crash in 2008. The focus must be on deploying the right technology to compete and meet the ever-evolving expectations of the consumer and the marketplace. The vision of the CIO can now either make or break the success of any company.

CIOs are driving a much larger part of the company strategy in every bank, particularly in determining how to either compete against or collaborate with fintechs and non-traditional banking providers. As a result, IT teams are growing. The skill sets required to drive company strategy forward using technology are evolving, and jobs in these areas have to be created. In fact, there aren’t enough qualified candidates to fill the roles they’ve already developed.

Meeting this need will require a pivot in how people are trained and which skills they’re looking to develop as they enter into the job market. Whether it’s data science, ML, AI (dare I say, blockchain), all of these new technologies need to be built and implemented by humans. The light bulb replaced candles, but the energy industry grew – it did not shrink.

Innovation breeds optimism

As a “glass half-full” optimist and believer that change is good, I see nothing but opportunity in what’s happening with technology in every industry – including financial services. I know my life is getting easier and more efficient because I can shop from my phone for almost anything, or find a doctor and make an appointment in 10 minutes with an app. If I forget my credit card out on my morning run, I can use my phone to buy a bottle of water or pick up a bag of dog food on my way home. Banking is changing, every industry is changing – that’s Industry 4.0.  And the best part is that it’s also improving lives in banking in ways never thought possible.

I hope you’re as pumped as I am now.

Where do you get started? SAP Leonardo is our methodology through which innovative, new solutions are being developed to solve business problems for our financial services customers. Whether through consulting or co-innovating with banks and fintechs, the sky is the limit. 

Planning on attending the SAPPHIRE NOW conference? SAP’s financial services team has developed a variety of cool use cases for banking that use AI and ML, some of which will be explored in the Banking Industry Campus. I hope you’ll visit the Web site and explore the session catalog for more information on SAPPHIRE NOW so you, too, can become an optimist.


Karen McDermott

About Karen McDermott

Karen McDermott is Global Head of Financial Services Industries Marketing and Communications at SAP, responsible for driving the growth of SAP's value proposition as a technology provider, trusted business partner, and thought leader for the financial services industry.

From Digital To Intelligent: Making The Most Of Machine Learning

Dr. Markus Noga

Businesses are no longer just digital – they are becoming increasingly intelligent. A recent survey of 360 organizations by the Economist Intelligence Unit and SAP showed that, on average, 68% of them use machine learning to enhance their business processes. Now, businesses are moving beyond just improving performance across the existing business, instead moving towards developing entirely new business models, optimized processes, and value propositions.

For businesses, machine learning can enable software to adapt and improve the execution of tasks and processes autonomously. This saves time and money while empowering employees to focus on value-adding, strategic, and creative tasks. Businesses that have already benefitted from the power of machine learning are called Fast Learners, and they experience benefits from improved customer satisfaction and increased profitability. Some have improved customer support with machine learning chatbots, and nearly half of all Fast Learners expect revenue growth of more than six percent from 2018 to 2019.

But what sets Fast Learners apart from their competition? What makes them so willing to take the perceived – yet much lower than expected – risk of embracing this new technology? As I work with them in implementing machine learning across their businesses, five key traits become more obvious every day:

The five traits of fast learners

  1. C-level, strategic priority: Fast Learners’ senior-most management sees the strategic value of machine learning and fosters a workplace environment that is not afraid of change.
  1. Increased competitive differentiation: Fast Learners see machine learning as a pragmatic yet innovative way to stand out in a crowded market, not as a gimmick or fad.
  1. New revenue and profitability: Machine learning is a valuable source of revenue and profitability for Fast Learners. They look to bring about fundamental, rather than incremental, change and believe machine learning’s potential in business model innovation is enormous.
  1. Key processes close to home: Spending money on locally sourced business functions is important to Fast Learners – they spend more on local functions than they do on ones from low-cost regions.
  1. Enterprise-wide strategy: Fast Learners look at what machine learning can do for their business in a holistic way rather than forcing it into a purpose that may not be the best fit.

Of these traits, I believe that C-level strategic priority and enterprise-wide strategy are the most important. These two traits often go hand in hand – where senior management is aware of the opportunities and limitations of machine learning, they are more likely to look at what the technology can do for their business in a holistic way with enterprise-wide strategy. The other traits simply follow naturally.

Embracing the hype for improved business practices

Equally apparent are the reasons businesses do not implement machine learning. Most commonly, they lack those aforementioned traits. But often, there are also misconceptions about the effort and cost required to implement machine learning solutions. Many simply don’t know where to start or are afraid to fall victim to yet another technological fad.

But the machine learning hype is well-warranted. Fast Learners who began their machine learning journey before most people had ever even heard of the technology have since created a lasting impact across the breadth of their organizations that goes far beyond hype. For example, one Chinese shoe company used machine learning to enable customers to design their own shoes and wear them within one week. Your business can launch such lasting innovations, too.

As you embark on your own machine learning journey, I recommend taking a closer look at what other organizations in your space have done. Are they using it to better connect with customers through smart marketing campaigns? Are they better responding to customer concerns after integrating it with contact centers? You’ll soon realize that there are plenty of low-risk machine learning initiatives you can pilot as you test the waters.

Interested in learning more about the five traits of Fast Learners? Read the study here


Dr. Markus Noga

About Dr. Markus Noga

Dr. Markus Noga is vice president of Machine Learning at SAP. Machine learning (ML) applies deep learning, machine learning, and advanced data science to solve business challenges. The ML team aspires to building SAP’s next growth business in intelligent solutions, and works closely with existing product units and platform teams to deliver business value to their customers. Part of the SAP Innovation Center Network (ICN), the Machine Learning team operates as a lean startup within SAP with sites in Germany, Israel, Singapore, and Palo Alto.

The Human Angle

By Jenny Dearborn, David Judge, Tom Raftery, and Neal Ungerleider

In a future teeming with robots and artificial intelligence, humans seem to be on the verge of being crowded out. But in reality the opposite is true.

To be successful, organizations need to become more human than ever.

Organizations that focus only on automation will automate away their competitive edge. The most successful will focus instead on skills that set them apart and that can’t be duplicated by AI or machine learning. Those skills can be summed up in one word: humanness.

You can see it in the numbers. According to David J. Deming of the Harvard Kennedy School, demand for jobs that require social skills has risen nearly 12 percentage points since 1980, while less-social jobs, such as computer coding, have declined by a little over 3 percentage points.

AI is in its infancy, which means that it cannot yet come close to duplicating our most human skills. Stefan van Duin and Naser Bakhshi, consultants at professional services company Deloitte, break down artificial intelligence into two types: narrow and general. Narrow AI is good at specific tasks, such as playing chess or identifying facial expressions. General AI, which can learn and solve complex, multifaceted problems the way a human being does, exists today only in the minds of futurists.

The only thing narrow artificial intelligence can do is automate. It can’t empathize. It can’t collaborate. It can’t innovate. Those abilities, if they ever come, are still a long way off. In the meantime, AI’s biggest value is in augmentation. When human beings work with AI tools, the process results in a sort of augmented intelligence. This augmented intelligence outperforms the work of either human beings or AI software tools on their own.

AI-powered tools will be the partners that free employees and management to tackle higher-level challenges.

Those challenges will, by default, be more human and social in nature because many rote, repetitive tasks will be automated away. Companies will find that developing fundamental human skills, such as critical thinking and problem solving, within the organization will take on a new importance. These skills can’t be automated and they won’t become process steps for algorithms anytime soon.

In a world where technology change is constant and unpredictable, those organizations that make the fullest use of uniquely human skills will win. These skills will be used in collaboration with both other humans and AI-fueled software and hardware tools. The degree of humanness an organization possesses will become a competitive advantage.

This means that today’s companies must think about hiring, training, and leading differently. Most of today’s corporate training programs focus on imparting specific knowledge that will likely become obsolete over time.

Instead of hiring for portfolios of specific subject knowledge, organizations should instead hire—and train—for more foundational skills, whose value can’t erode away as easily.

Recently, educational consulting firm Hanover Research looked at high-growth occupations identified by the U.S. Bureau of Labor Statistics and determined the core skills required in each of them based on a database that it had developed. The most valuable skills were active listening, speaking, and critical thinking—giving lie to the dismissive term soft skills. They’re not soft; they’re human.


This doesn’t mean that STEM skills won’t be important in the future. But organizations will find that their most valuable employees are those with both math and social skills.

That’s because technical skills will become more perishable as AI shifts the pace of technology change from linear to exponential. Employees will require constant retraining over time. For example, roughly half of the subject knowledge acquired during the first year of a four-year technical degree, such as computer science, is already outdated by the time students graduate, according to The Future of Jobs, a report from the World Economic Forum (WEF).

The WEF’s report further notes that “65% of children entering primary school today will ultimately end up working in jobs that don’t yet exist.” By contrast, human skills such as interpersonal communication and project management will remain consistent over the years.

For example, organizations already report that they are having difficulty finding people equipped for the Big Data era’s hot job: data scientist. That’s because data scientists need a combination of hard and soft skills. Data scientists can’t just be good programmers and statisticians; they also need to be intuitive and inquisitive and have good communication skills. We don’t expect all these qualities from our engineering graduates, nor from most of our employees.

But we need to start.

From Self-Help to Self-Skills

Even if most schools and employers have yet to see it, employees are starting to understand that their future viability depends on improving their innately human qualities. One of the most popular courses on Coursera, an online learning platform, is called Learning How to Learn. Created by the University of California, San Diego, the course is essentially a master class in human skills: students learn everything from memory techniques to dealing with procrastination and communicating complicated ideas, according to an article in The New York Times.

Attempting to teach employees how to make behavioral changes has always seemed off-limits to organizations—the province of private therapists, not corporate trainers. But that outlook is changing.

Although there is a longstanding assumption that social skills are innate, nothing is further from the truth. As the popularity of Learning How to Learn attests, human skills—everything from learning skills to communication skills to empathy—can, and indeed must, be taught.

These human skills are integral for training workers for a workplace where artificial intelligence and automation are part of the daily routine. According to the WEF’s New Vision for Education report, the skills that employees will need in the future fall into three primary categories:

  • Foundational literacies: These core skills needed for the coming age of robotics and AI include understanding the basics of math, science, computing, finance, civics, and culture. While mastery of every topic isn’t required, workers who have a basic comprehension of many different areas will be richly rewarded in the coming economy.
  • Competencies: Developing competencies requires mastering very human skills, such as active listening, critical thinking, problem solving, creativity, communication, and collaboration.
  • Character qualities: Over the next decade, employees will need to master the skills that will help them grasp changing job duties and responsibilities. This means learning the skills that help employees acquire curiosity, initiative, persistence, grit, adaptability, leadership, and social and cultural awareness.


The good news is that learning human skills is not completely divorced from how work is structured today. Yonatan Zunger, a Google engineer with a background working with AI, argues that there is a considerable need for human skills in the workplace already—especially in the tech world. Many employees are simply unaware that when they are working on complicated software or hardware projects, they are using empathy, strategic problem solving, intuition, and interpersonal communication.

The unconscious deployment of human skills takes place even more frequently when employees climb the corporate ladder into management. “This is closely tied to the deeper difference between junior and senior roles: a junior person’s job is to find answers to questions; a senior person’s job is to find the right questions to ask,” says Zunger.

Human skills will be crucial to navigating the AI-infused workplace. There will be no shortage of need for the right questions to ask.

One of the biggest changes narrow AI tools will bring to the workplace is an evolution in how work is performed. AI-based tools will automate repetitive tasks across a wide swath of industries, which means that the day-to-day work for many white-collar workers will become far more focused on tasks requiring problem solving and critical thinking. These tasks will present challenges centered on interpersonal collaboration, clear communication, and autonomous decision-making—all human skills.

Being More Human Is Hard

However, the human skills that are essential for tomorrow’s AI-ified workplace, such as interpersonal communication, project planning, and conflict management, require a different approach from traditional learning. Often, these skills don’t just require people to learn new facts and techniques; they also call for basic changes in the ways individuals behave on—and off—the job.

Attempting to teach employees how to make behavioral changes has always seemed off-limits to organizations—the province of private therapists, not corporate trainers. But that outlook is changing. As science gains a better understanding of how the human brain works, many behaviors that affect employees on the job are understood to be universal and natural rather than individual (see “Human Skills 101”).

Human Skills 101

As neuroscience has improved our understanding of the brain, human skills have become increasingly quantifiable—and teachable.

Though the term soft skills has managed to hang on in the popular lexicon, our understanding of these human skills has increased to the point where they aren’t soft at all: they are a clearly definable set of skills that are crucial for organizations in the AI era.

Active listening: Paying close attention when receiving information and drawing out more information than received in normal discourse

Critical thinking: Gathering, analyzing, and evaluating issues and information to come to an unbiased conclusion

Problem solving: Finding solutions to problems and understanding the steps used to solve the problem

Decision-making: Weighing the evidence and options at hand to determine a specific course of action

Monitoring: Paying close attention to an issue, topic, or interaction in order to retain information for the future

Coordination: Working with individuals and other groups to achieve common goals

Social perceptiveness: Inferring what others are thinking by observing them

Time management: Budgeting and allocating time for projects and goals and structuring schedules to minimize conflicts and maximize productivity

Creativity: Generating ideas, concepts, or inferences that can be used to create new things

Curiosity: Desiring to learn and understand new or unfamiliar concepts

Imagination: Conceiving and thinking about new ideas, concepts, or images

Storytelling: Building narratives and concepts out of both new and existing ideas

Experimentation: Trying out new ideas, theories, and activities

Ethics: Practicing rules and standards that guide conduct and guarantee rights and fairness

Empathy: Identifying and understanding the emotional states of others

Collaboration: Working with others, coordinating efforts, and sharing resources to accomplish a common project

Resiliency: Withstanding setbacks, avoiding discouragement, and persisting toward a larger goal

Resistance to change, for example, is now known to result from an involuntary chemical reaction in the brain known as the fight-or-flight response, not from a weakness of character. Scientists and psychologists have developed objective ways of identifying these kinds of behaviors and have come up with universally applicable ways for employees to learn how to deal with them.

Organizations that emphasize such individual behavioral traits as active listening, social perceptiveness, and experimentation will have both an easier transition to a workplace that uses AI tools and more success operating in it.

Framing behavioral training in ways that emphasize its practical application at work and in advancing career goals helps employees feel more comfortable confronting behavioral roadblocks without feeling bad about themselves or stigmatized by others. It also helps organizations see the potential ROI of investing in what has traditionally been dismissed as touchy-feely stuff.

In fact, offering objective means for examining inner behaviors and tools for modifying them is more beneficial than just leaving the job to employees. For example, according to research by psychologist Tasha Eurich, introspection, which is how most of us try to understand our behaviors, can actually be counterproductive.

Human beings are complex creatures. There is generally way too much going on inside our minds to be able to pinpoint the conscious and unconscious behaviors that drive us to act the way we do. We wind up inventing explanations—usually negative—for our behaviors, which can lead to anxiety and depression, according to Eurich’s research.

Structured, objective training can help employees improve their human skills without the negative side effects. At SAP, for example, we offer employees a course on conflict resolution that uses objective research techniques for determining what happens when people get into conflicts. Employees learn about the different conflict styles that researchers have identified and take an assessment to determine their own style of dealing with conflict. Then employees work in teams to discuss their different styles and work together to resolve a specific conflict that one of the group members is currently experiencing.

How Knowing One’s Self Helps the Organization

Courses like this are helpful not just for reducing conflicts between individuals and among teams (and improving organizational productivity); they also contribute to greater self-awareness, which is the basis for enabling people to take fullest advantage of their human skills.

Self-awareness is a powerful tool for improving performance at both the individual and organizational levels. Self-aware people are more confident and creative, make better decisions, build stronger relationships, and communicate more effectively. They are also less likely to lie, cheat, and steal, according to Eurich.

It naturally follows that such people make better employees and are more likely to be promoted. They also make more effective leaders with happier employees, which makes the organization more profitable, according to research by Atuma Okpara and Agwu M. Edwin.

There are two types of self-awareness, writes Eurich. One is having a clear view inside of one’s self: one’s own thoughts, feelings, behaviors, strengths, and weaknesses. The second type is understanding how others view us in terms of these same categories.

Interestingly, while we often assume that those who possess one type of awareness also possess the other, there is no direct correlation between the two. In fact, just 10% to 15% of people have both, according to a survey by Eurich. That means that the vast majority of us must learn one or the other—or both.

Gaining self-awareness is a process that can take many years. But training that gives employees the opportunity to examine their own behaviors against objective standards and gain feedback from expert instructors and peers can help speed up the journey. Just like the conflict management course, there are many ways to do this in a practical context that benefits employees and the organization alike.

For example, SAP also offers courses on building self-confidence, increasing trust with peers, creating connections with others, solving complex problems, and increasing resiliency in the face of difficult situations—all of which increase self-awareness in constructive ways. These human-skills courses are as popular with our employees as the hard-skill courses in new technologies or new programming techniques.

Depending on an organization’s size, budget, and goals, learning programs like these can include small group training, large lectures, online courses, licensing of third-party online content, reimbursement for students to attain certification, and many other models.

Human Skills Are the Constant

Automation and artificial intelligence will change the workplace in unpredictable ways. One thing we can predict, however, is that human skills will be needed more than ever.

The connection between conflict resolution skills, critical thinking courses, and the rise of AI-aided technology might not be immediately obvious. But these new AI tools are leading us down the path to a much more human workplace.

Employees will interact with their computers through voice conversations and image recognition. Machine learning will find unexpected correlations in massive amounts of data but empathy and creativity will be required for data scientists to figure out the right questions to ask. Interpersonal communication will become even more important as teams coordinate between offices, remote workplaces, and AI aides.

While the future might be filled with artificial intelligence, deep learning, and untold amounts of data, uniquely human capabilities will be the ones that matter. Machines can’t write a symphony, design a building, teach a college course, or manage a department. The future belongs to humans working with machines, and for that, you need human skills. D!


About the Authors

Jenny Dearborn is Chief Learning Officer at SAP.

David Judge is Vice President, SAP Leonardo, at SAP.

Tom Raftery is Global Vice President and Internet of Things Evangelist at SAP.

Neal Ungerleider is a Los Angeles-based technology journalist and consultant.

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.

Tags:

HR In The Age Of Digital Transformation

Neha Makkar Patnaik

HR has come a long way from the days of being called Personnel Management. It’s now known as People & Culture, Employee Experience, or simply People, and the changes in the last few years have been especially far-reaching, to say the least; seismic even.

While focused until recently on topics like efficiency and direct access to HR data and services for individual employees, a new and expanded HR transformation is underway, led by employee experience, cloud capabilities including mobile and continuous upgrades, a renewed focus on talent, as well as the availability of new digital technologies like machine learning and artificial intelligence. These capabilities are enabling HR re-imagine new ways of delivering HR services and strategies throughout the organization. For example:

  • Use advanced prediction and optimization technologies to shift focus from time-consuming candidate-screening processes to innovative HR strategies and business models that support growth
  • Help employees with tailored career paths, push personalized learning recommendations, suggest mentors and mentees based on skills and competencies
  • Predict flight risk of employees and prescribe mitigation strategies for at-risk talent
  • Leverage intelligent management of high-volume, rules-based events with predictions and recommendations

Whereas the traditional view of HR transformation was all about doing existing things better, the next generation of HR transformation is focused on doing completely new things.

These new digital aspects of HR transformation do not replace the existing focus on automation and efficiency. They work hand in hand and, in many cases, digital technologies can further augment automation. Digital approaches are becoming increasingly important, and a digital HR strategy must be a key component of HR’s overall strategy and, therefore, the business strategy.

For years, HR had been working behind a wall, finally got a seat at the table, and now it’s imperative for CHROs to be a strategic partner in the organization’s digital journey. This is what McKinsey calls “Leading with the G-3” in An Agenda for the Talent-First CEO, in which the CEO, CFO, and CHRO (i.e., the “G-3”) ensure HR and finance work in tandem, with the CEO being the linchpin and the person who ensures the talent agenda is threaded into business decisions and not a passive response or afterthought.

However, technology and executive alignment aren’t enough to drive a company’s digital transformation. At the heart of every organization are its people – its most expensive and valuable asset. Keeping them engaged and motivated fosters an innovation culture that is essential for success. This Gallup study reveals that a whopping 85% of employees worldwide are performing below their potential due to engagement issues.

HR experiences that are based on consumer-grade digital experiences along with a focus on the employee’s personal and professional well-being will help engage every worker, inspiring them to do their best and helping them turn every organization’s purpose into performance. Because, we believe, purpose drives people and people drive business results.

Embark on your HR transformation journey

Has your HR organization created a roadmap to support the transformation agenda? Start a discussion with your team about the current and desired state of HR processes using the framework with this white paper.

Also, read SAP’s HR transformation story within the broader context of SAP’s own transformation.


Neha Makkar Patnaik

About Neha Makkar Patnaik

Neha Makkar Patnaik is a principal consultant at SAP Labs India. As part of the Digital Transformation Office, Neha is responsible for articulating the value proposition for digitizing the office of the CHRO in alignment with the overall strategic priorities of the organization. She also focuses on thought leadership and value-based selling programs for retail and consumer products industries.